报告题目: Empirical likelihood in semiparametric models

报告人：薛留根教授

报告摘要:

In this talk, we discuss the empirical likelihood based inference problem in semiparametric models. Firstly, we investigate the empirical likelihood based inference for the parameters in a partially linear single-index model. we propose a bias correction method to achieve that the empirical likelihood ratio has standard chi-square limit. Secondly, we investigate the empirical likelihood-based inference for a varying coefficient model with longitudinal data. we propose three empirical likelihood ratios: the naive empirical likelihood ratio, the mean-corrected empirical likelihood ratio and the residual-adjusted empirical likelihood ratio, and show that these ratios have chi-square limits. In addition, when some components are of particular interest, we suggest the mean-corrected and residual-adjusted partial empirical likelihood ratios for the construction of the confidence regions/intervals. A simulation study is undertaken to compare the empirical likelihood and the normal approximation methods in terms of coverage accuracies and average areas/widths of confidence regions/intervals. An example in epidemiology is used for illustration.

报告时间：2019年6月10日 16:30--17:30

报告地点：统计学院213会议室

报告人简介：薛留根，教授，博士生导师，北京工业大学统计学一级学科博士点负责人。主要学术兼职：中国现场统计研究会理事及生存分析分会副理事长等。主持完成和在研的国家和省部级科研项目15项。出版著作8部（独著6部），其中3部专著。在《Journal of the American Statistical Association》、《Journal of the Royal Statistical Society，Series B》、《The Annals of Statistics》、《Biometrika》等国内外学术期刊上发表学术论文200余篇，其中2篇为高被引论文。以第一完成人获教育部自然科学二等奖和全国统计科学研究优秀成果一等奖各1项。已招收研究生65人，其中博士研究生20人，硕士研究生45人；指导的研究生中1人获北京市优秀博士学位论文及全国优秀博士学位论文提名奖，1人获全国统计科学研究优秀成果博士学位论文二等奖。